Characterization of fine particulate matter from indoor cooking with solid biomass fuels

Abstract Household burning of solid biomass fuels emits pollution particles that are a huge health risk factor, especially in low‐income countries (LICs) such as those in Sub‐Saharan Africa. In epidemiological studies, indoor exposure is often more challenging to assess than outdoor exposure. Laboratory studies of solid biomass fuels, performed under real‐life conditions, are an important path toward improved exposure assessments. Using on‐ and offline measurement techniques, particulate matter (PM) from the most commonly used solid biomass fuels (charcoal, wood, dung, and crops residue) was characterized in laboratory settings using a way of burning the fuels and an air exchange rate that is representative of real‐world settings in low‐income countries. All the fuels generated emissions that resulted in concentrations which by far exceed both the annual and the 24‐hour‐average WHO guidelines for healthy air. Fuels with lower energy density, such as dung, emitted orders of magnitude more than, for example, charcoal. The vast majority of the emitted particles were smaller than 300 nm, indicating high deposition in the alveoli tract. The chemical composition of the indoor pollution changes over time, with organic particle emissions often peaking early in the stove operation. The chemical composition of the emitted PM is different for different biomass fuels, which is important to consider both in toxicological studies and in source apportionment efforts. For example, dung and wood yield higher organic aerosol emissions, and for dung, nitrogen content in the organic PM fraction is higher than for the other fuels. We show that aerosol mass spectrometry can be used to differentiate stove‐related emissions from fuel, accelerant, and incense. We argue that further emission studies, targeting, for example, vehicles relevant for LICs and trash burning, coupled with field observations of chemical composition, would advance our understanding of air pollution in LIC. We believe this to be a necessary step for improved air quality policy.


| INTRODUC TI ON
It is well established that household burning of solid biomass fuels, such as charcoal, wood, crops residue, and dung, emits high levels of pollutants that are detrimental to human health. The World Health Organization (WHO) estimates that almost 3 billion people globally are dependent on solid biomass fuels for cooking and heating. 1 According to the International Energy Agency (IEA), 2 900 million people in Sub-Saharan Africa relied on solid biomass fuels in 2018.
In Ethiopia, that percentage is >90% according to WHO. 3 Africa is, hence, burdened by air pollution emissions from biomass burning, 4 and due to the rapid increase in population, solid biomass fuel emissions are expected to escalate even more. This is mainly due to that the frequent challenges with erratic electric power 5 are forecasted to remain; the IEA 2 estimates that by 2030, over 600 million people in Africa will still not have access to reliable electric power.
Many low-income countries (LICs), where solid biomass fuel is used for cooking, still have a long way to go toward compliance with the "strong recommendation" from WHO that indoor PM 2.5 (particulate matter with an aerodynamic diameter <2.5 μm) must be reduced to values close to 10 μg/m 36 to avert most of the adverse effect on health caused by household air pollution, and an even longer way toward compliance with the ambient PM 2.5 guideline of 5 μg/m 3 as annual average. 7 Taking Ethiopia as example, in Addis Ababa the average particulate matter (PM) levels during coffee making using charcoal found in one study 8 were 905 μg/m 3 in the personal breathing zone and 845 μg/m 3 in the room's background air. In another Addis Ababa study, 9 indoor PM 2.5 measured in 59 homes in slum neighborhoods showed a 24-h average of 818 μg/m 3 . A quadruple increase in PM 2.5 was shown when animal dung rather than other biomass fuels was used. Additionally, a third study 10 found that women are exposed to PM 2.5 levels 7 times higher than what men are in Uganda and Ethiopia.
From a health perspective, exposure to household air pollution is globally the single most important environmental risk factor. 11 Most particulate matter emitted from solid biomass fuels is smaller than 2.5 μm, 12 enabling a predominant deposition in the deep lung. In 2012, household air pollution was responsible for 4.3 million deaths globally and nearly 5% of the global disease burden. 13 Of these deaths, almost 600 000 occurred in Africa. 13 Huang et al 14 15 looking specifically at Africa, highlights evidence for the association between household air pollution and respiratory risks, and found that both upper and lower airway respiratory infections were associated with household air pollution. Furthermore, they found that both nasopharyngeal cancer and lung cancer were strongly associated with pollution from charcoal burning, and that chronic lung diseases, such as chronic obstructive pulmonary disease (COPD) and bronchiectasis, were associated with cooking using solid fuels. In a recent descriptive, cross-sectional study 16 of respiratory symptoms in 545 Ethiopian women, Tamire et al found that cough, phlegm, nose irritation, and eye irritation were significantly more prevalent among women using solid biomass fuels than among users of cleaner fuels such as liquefied petroleum gas. Using spirometry, they also found significantly lower forced expiratory volume (FEV) among solid biofuel users. Children, too, suffer respiratory effects of household air pollution from solid biomass fuels. A recent review 17 focused on Ethiopia found that the overall pooled prevalence of acute respiratory infection in children under five, due to living in homes where cooking was done using solid biomass fuels, was 22%. Furthermore, there is a range of adverse health effects, other than respiratory, associated with solid biomass fuel exposure.
A systematic review from 2020 found positive associations between wood smoke and increased blood pressure, low birth weight, esophageal cancer, sick building syndrome, non-syndromic cleft lip and/ or cleft palate, and under-five mortality. That indoor air pollution from solid biomass fuels is a strong risk factor for hypertension was also shown by, for example, Li et al. 18 A recent health impact assessment study 19 estimated the burden of disease of acute lower respiratory infections, chronic obstructive pulmonary disease, ischemic heart disease, lung cancer, and stroke in an Ethiopian cohort of 2000 women and concluded that the disability-adjusted life-years (DALYs) lost per 100 000 women ranged between 6000 and 9000, per disease.
Additionally, household air pollution contributes to the outdoor air pollution-in rural areas it may be the major outdoor air pollution source-thereby household air pollution is responsible of an additional 400 000 deaths annually (12% of the total number of deaths attributed to outdoor air pollution). Black carbon, which is one of the main constituents of PM emitted from solid biomass fuels, have a potentially large but poorly quantified climate warming effect. As shown by Bond 20 and highlighted by, for example, Pokhrel,4 Africa is the largest global source of carbon emissions from solid biomass fuel, with residential solid biomass fuels being responsible for up to 80% of Africa's black carbon emissions.

Practical Implications
This study, looking at emission levels and physicochemical properties of airborne particles smaller than 2.5 μm, was conducted at an air exchange rate of 15 h −1 , which is the average air exchange rate that was found in our recent field studies (26 homes) in Ethiopia. That means that the particle concentrations in the measurement volume, and the aerosol dynamics taking place, are relevant for real-world indoor air in a Sub-Sahara African county like Ethiopia. The results from this study can be used both for indoor exposure assessment in epidemiological studies, for source apportionment, and as input for more detailed toxicological studies of solid biomass emissions.
Cooking in Ethiopia is commonly conducted using charcoal in a traditional stove or wood, dung, or crop residue in a 3-stone setup.
When using a stove, the charcoal is commonly ignited outdoors to reduce exposure. A piece of plastic material, small wood sticks, cardboard, or sometimes a very small amount of gasoline or kerosene is used to ignite the charcoal, and air is supplied mechanically to assist the ignition. After ignition, the cook stove is moved indoors for cooking. In the rural parts of Ethiopia, the household energy source is mainly wood, dung, and crops residue. In these cases, 3-stone setups are used, commonly in a separate room attached to the main room, or in the same room as family share for reading, feeding as well as sleeping. In the highland parts of The aim of this study was to characterize airborne PM 2.5 generated under realistic conditions in laboratory settings, to provide relevant data for indoor exposure assessments in epidemiological studies and for source apportionment studies in LICs.

| Solid biomass fuels
The following biomass fuels were brought from central Ethiopia: The fuels were separated into batches large enough to represent a cooking event. Each batch were weighed and kept in the laboratory (at a temperature and relative humidity of approximately 20°C and 40%, respectively) until being used.
Additionally, thin plastic bags that are often used in Ethiopia to start the charcoal fire was brought, as well as five different types of aromatic resins, in Ethiopia these are added to the charcoal directly after cooking or coffee preparation to spread their scents in the room.

| Combustion setup
The biomass fuel aerosols were generated in a 1.33 m 3 stainless steel chamber. Pressurized air, filtered through a HEPA-filter, was deliv- It can be entered via an antechamber, and the door is airtight. To avoid contamination of the surrounding laboratory, a slight underpressure is constantly kept in the chamber. The chamber is supplied with a controlled flow of clean HEPA-and active carbon-filtered air by a custom-built conditioning system. The flow of generated aerosol is mixed into the flow from the conditioning system just before entering the chamber at roof level. A schematic of the generation system and measurement volume is shown in Figure 1. We adapted a method to analyze PM 2.5 particle decay rates measured with DustTrak in 26 homes in Adama, Ethiopia, after cooking (manuscript in preparation) and could thereby assess an average AER of 14.11 h −1 (min 3.7 and max 39.4 h −1 ). Hence, to simulate conditions in an average Ethiopian home, the AER in the chamber was set to 15 h −1 (the volume of the measurement volume is also in the range of typical rooms in which cooking occurs).
The two different types of charcoal were burnt in a traditional stove (with the Amharic name Kassel Mendeja) of clay and thin metallic sheet ( Figure 2) obtained at Adama market. The stove was operated by a scientist with real-world experience of cooking with this equipment. The distance between the top of the charcoal layer and the cauldron placed on the stove (see below) was 1-3 cm. The non-charcoal fuels: wood, dung, and crops residue were burnt using a 3-stone setup as is commonly done in Sub-Saharan Africa (SSA), with approximately 10 cm between fuel and cauldron. To avoid contamination from accelerants, the charcoal and dung were lit using a heating gun. The wood and crop residue were lit using matches.
For the charcoal stove, a modified water boiling test was employed. Each experiment was initiated by a "cold start" sequence in which a cold stove was fueled with approximately four hundred grams of charcoal, and lit order to bring two liters of room temperature water to boiling point. After this, a "hot start" was performed by replacing the water such that the (now hot) stove again brings two liters of room temperature water to boiling point (see Figures 5 and 7). This second batch of water was left on the stove simmering until the charcoal was consumed. The main deviation from the standard water boiling test 24 was that we used a lid (as cauldron users are prone to do in everyday use) to reduce heat lost from the water. For the non-charcoal fuels, our full modified water boiling test was found unfeasible, but the cauldron and the 2 liters of water were kept, as quenching of flames likely influences emissions. Non-charcoal fuels were thus burned in a similar manner as the charcoal, the difference being we did not achieve full test cycles (cold start and hot start described above).
In selected experiments, we also explored the effects of plastic bags (procured at the Adama market) used as accelerants to light the stove, as this practice is common and likely to result in emissions.
Furthermore, we also investigated particle emissions from aromatic resins (also from the Adama market), which are added by some stove users to the charcoal post-cooking/coffee ceremony to produce fragrance. These emissions are not included in the modified water boiling tests reported, for those we aimed to characterize fuel emissions only, for clarity. We include the bag and resin emissions as examples of non-fuel emissions from stove operation.  I G U R E 1 Schematic view of the complete generation/measurement system, including the measurement equipment, all highly time resolved. AE33, black/brown carbon; AMS, aerosol mass spectrometer; PM, particulate matter; PM 2.5 , particulate matter with an aerodynamic diameter < 2.5 μm; SMPS, scanning mobility particle sizer; TEOM, tapered element oscillating microbalance; ULPA, ultra low particulate air filter.

F I G U R E 2 Traditional
Ethiopian stove for cooking with charcoal. Approximate height and diameter: 25 cm.
to study its feasibility in monitoring solid biomass fuel emissions.
The DustTrak was zero-calibrated prior to each experiment using a HEPA filter according to the standard procedure recommended by the manufacturer.
Mobility size distributions and number concentrations of particles 10-500 nm were measured by a Scanning Mobility Particle Sizer (SMPS, Model 3082, TSI, Shoreview, MN, USA), consisting of a 44 cm differential mobility analyzer (DMA, Model 3082) and a condensation particle counter (CPC, Model 3772). The aerosol flow rate was 0.35 L.min −1 , and the sheet flow was 1.05 L.min −1 . An aerosol particle sizer (APS model 3321, TSI Inc., USA) was used in early experiments to verify that there were very low concentrations above 500 nm (data not shown) in our setup.
An aerosol mass spectrometer (AMS, Aerodyne Inc., Billerica, MA, USA) was used for online chemical characterization of the emitted PM. The ionization efficiency (sensitivity) of the instrument was calibrated using 300 nm ammonium nitrate particles, size selected with a differential mobility analyzer (DMA Model 3082) and counted by a condensation particle counter (CPC, Model 3772). A soot particle AMS was used, but here we report data recorded with the "soot module" (laser vaporizer) disengaged, hence only "non-refractory," which flash vaporizes at 600°C PM is included in the mass spectra. The vapors produced from the par-   to that the thermal-optical carbon analysis system was offline. In the PIXE analysis, conducted at the Division of Nuclear Physics at Lund University, a 2.55 MeV proton beam is used to generate elementspecific X-ray emission lines. 26 In these experiments, PIXE was used to compare the relative abundance of different species from different biomass fuels.

| Off-line measurements
Additionally, a high-volume sampler (BGI 900 BGI Inc., Waltham, MA, USA) was used at 900 L.min −1 , to collect PM 2.5 from the different biomass fuels for later toxicological in-vitro studies (not presented here).

| Emission factors and exposure levels
Emission factors (in units of g PM 2.5 /kg fuel) were calculated based on TEOM (see Figure 3) and DustTrak data. The DustTrak gave similar emission factor results for charcoal (the DustTrak to TEOM ratio was 0.8-1.1) but yielded threefold higher emission factor values for wood and dung, with a DustTrak to TEOM ratio of 2.8 for both biomass fuels, highlighting the need to validate DustTrak measurements for each type of aerosol investigated.
From the TEOM data, average PM 2.5 levels in the measurement volume (the simulated cooking environment) were calculated during a full burning event (from that the concentration started to increase to when the concentration had declined back to baseline) for the different fuels. The results are shown in Table 1.
The PM 2.5 mass concentration levels generated from wood are more than one order of magnitude higher than from charcoal, and the levels generated by dung burning are yet another order of mag-

| Size distributions
We found, consistent with many previous studies, that solid biomass fuels predominantly generate airborne particles of small sizes. Figure 4 shows an example of size distributions for particles from wood and dung combustion. Both size distributions are clearly multimodal, and the dominating mode, in terms of particle number, is below 100 nm.
Other experiments (not shown) in which transport from generation volume into measurement volume (i.e., the simulated residence air) was less rapid (see "combustion set-up" in the method section) produced monomodal distributions with larger particles, though never larger than a few hundred nanometers in diameter. This reflects the fact that coagulation between particles tends to produce larger sizes as time passes by. For example, downwind of the cooking, or after some time when lower PM levels remain in the residence. As the size distributions from different fuels were not that different to begin with, and end up even more similar (and unimodal), particle size is clearly a poor marker for their origin.

| Chemical composition
The chemical composition of the PM 2.5 emitted from charcoal combustion varies with time after ignition. Figure 5 shows an example of charcoal combustion, where it can be seen that there is an initial high peak in the PM 2.5 mass concentration, with a high fraction of organic compounds. This is true also for the other fuels (not shown here). This peak is followed by a build-up of inorganic PM. Chloride level is the next to rise, peaking around half the peak organic concentration.
Sulfate rises next, to approximately half of peak chloride concentration. This is followed by a smaller amount of nitrates which builds up over longer time.
Charcoal is different from the other fuels in that the nonrefractory PM emitted contains comparable amounts of organic and inorganic material, while the others are dominated by organics, as can be seen in Figure 6. Eucalyptus and Acacia charcoal combustion produced rather similar mass spectra. The main peaks are HCl + (at m/z 36) and K + (at m/z 39), with Eucalyptus yielding higher K + than HCl + , and the opposite (HCl + > K + ) for Acacia. has a strong contribution also from CH 2 NO 2 + (ca 40%). Overall nitrogen atoms account for ~7% of the signal in the dung-burning mass spectrum, which is unusually high for organic PM (as it is normally dominated by carbon, oxygen, and hydrogen). Crop residue emissions have about half the nitrogen contribution dung has, and in the wood and charcoal burning spectra, nitrogen is lower still.
From the PIXE analysis, it could be seen that all fuel emissions were dominated by potassium, chloride, phosphorous, and silica.
The two types of charcoal, as well as Milla wood, were more dominated by potassium than the others. It should be noted that PIXE is "blind" to the organic components shown in the AMS results ( Figures 5-7), which are very abundant in the non-charcoal emis- F I G U R E 4 Normalized size distributions from wood combustion and dung combustion measured by Scanning Mobility Particle Sizer (SMPS). The data are normalized to account for "bin width" and rescaled such that the highest value is 1.
A typical modified water boiling test with charcoal is illustrated in

| DISCUSS ION
In this study, we have looked at physicochemical properties of biofuel PM 2.5 relevant for exposure assessment and epidemiological studies. The PM 2.5 was generated in a laboratory setup under realistic conditions, that is, using a combustion initiation and procedure that is used in real life and studying the emissions at a real-world- done, but to use these emission factors, information on mass of fuel being used is needed. This information is seldom available since it is not feasible to ask all households that are part of a large cohort to weigh their fuel before igniting it, and to weigh the residues of the fuel after cooking. Information that is easily available is type of fuel used and time per day spent on cooking. We suggest that using an approach that assesses PM 2.5 concentrations in a controlled laboratory volume with a relevant air exchange rate, in our case 15 h −1 , might be a more feasible way to assess indoor exposure in large LIC cohorts. Further work is recommended comparing ways of assessing indoor exposure by combining field and laboratory experiments to find the best strategy to advance epidemiology.

F I G U R E 5
Time resolved chemical composition of PM from Eucalyptus charcoal burning measured by the AMS. Chemical species concentration (A) and fraction (B). Non-refractory refers to readily vaporized (at 600°C).
From the time-resolved measurements (see Figure 5), it could clearly be seen that the peak exposures occur very early in the combustion process. The AMS measurements revealed that this is due to that volatile organic compounds, are released from the fuel in the heating process. A large amount of the exposure caused by this initial peak is avoided if the charcoal is ignited outdoors, as often is customary, and the stove carried indoors first when the charcoal is properly lit. We observed discrepancies between the PM concentrations as measured/estimated from TEOM, AMS, and dustrack. This highlights the need to use complementary particle measurements tor evaluation of data products through "closure" of, for example, PM 2.5 (making sure they are in fair agreement and quantifying their discrepancies). This should be seen as a long-term goal for ambient monitoring/field campaigns in SSA and an important aspect to consider in laboratory investigations of SSA-relevant sources.
As expected, the absolute majority of the particles generated in the study were smaller than 2.5 μm. In fact, an aerosol particle sizer (APS) was initially installed to measure number concentration and size distribution of particles 0.5-20 μm, but since almost no such particles were detected, the APS was not used for the rest of the F I G U R E 6 PM mass spectra from the investigated fuels, normalized for comparison (such that the sum is 1 for each spectrum, an at each mass to charge ratio, m/z, the signal fraction can be read.) Each spectrum is the average from one burning session, representative for the sessions with this fuel.
experiments. Other studies, such as, 12 with solid biomass fuels conducted in laboratory settings have come to the same conclusions regarding particle sizes. Chemical analyses are also of importance for source apportionment. For high-income countries, levoglucosan, which forms from thermal processing of cellulose, is often used as a tracer for wood burning. Judging from the low amounts of levoglucosan fragments Although our experiments show comparable levels of chloride and organic PM from charcoal combustion, it is likely atmospheric processing increases the organic fraction after emission through formation of secondary organic aerosol (gas phase emissions which age chemically into products which partitions into PM). However, as each household is primarily exposed to their own stove emissions, chloride is likely prevalent in the inhaled PM.

F I G U R E 7
Modified water boiling test using charcoal. Gas concentrations on top panel, "equivalent Black/Brown carbon" on middle panel (equivalent in the sense that although we measured light extinction, we report estimated mass concentration, as is commonly done) and PM 2.5 as well as "non-refractory" components therein. Details in main text.
Optical properties of PM are also used to apportion sources.
Our data suggest low brown carbon and even lower black carbon from charcoal while wood combustion produced more absorbing The lack of detailed exposure data is currently creating a negative feedback loop, which cross-disciplinary collaborations can help stop. As long as there is a lack of reliable data on exposure and of the health consequences of this exposure, public awareness and public concern will be missing. Without public concern, there will be no policy actions. If there are no policies that needs to be followed, there will be very little incentives to monitor the air and collect data, even though the costs in both health care and diminished economic productivity due to air pollution currently correspond to billions of USD 15 in several Sub-Saharan African countries. Apart from the economic costs, the human suffering from air pollution-related deaths and diseases is massive, and thus, science-based mitigation actions are clearly needed.
The severe lack of air pollution data from the SSA region is an obstacle for mitigation. We suggest that this is addressed by first focusing on the emission sources that are most common in the region. For indoor air pollution, this is biomass burning. When we can make exposure assessments where this source is included, we should move forward and address whether there are significant differences within the region, and also between the region and other regions, when it comes to, for example, differences in composition between fuels, user behavior, or combustion appliance, and the resulting emissions.

| CON CLUS IONS
All solid biomass fuels generated high levels of PM 2.5 . Concerning exposure, there is a big difference between the different fuels, with the less energy dense fuels, such as dung, generating the highest amount of PM 2.5 . The majority of PM from all the biomass fuels were smaller than 300 nm, a particle size fraction which has high deposition probability in the alveoli tract of the lung. It is high time to import state-of-the-art approaches from aerosol science, such as in-depth physicochemical characterization of different sources, to provide a more detailed exposure assessment beyond only mass concentration of PM 2.5 . Better understanding of real-world emissions and exposures are also much needed input to toxicological studies. Additionally, studies like this one helps us gain a better understanding of the links between activities (such as cooking and F I G U R E 8 PM mass spectra from non-fuel combustion emissions related to stove operation, resin and plastic bag. Normalized for comparison (such that the sum is 1 for each spectrum, and at each mass to charge ratio (m/z) the signal fraction can be read.) heating, transport, industry) and air pollution, which is much needed for policy making, not least in LMICs. In order to assess indoor exposure in detail using real-world like laboratory settings, as well as assess the health outcomes of that exposure and the underlying mechanisms, a close collaboration between aerosol science, epidemiology, and toxicology is necessary.

CO N FLI C T O F I NTE R E S T
We declare no conflict of interest.

DATA AVA I L A B I L I T Y S TAT E M E N T
The data that support the findings of this study are available from the corresponding author upon reasonable request.